This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. A CPM and Radial Atrophy Mapping Background: little information is available on the cerebral characteristics of familial mood disorders. Medial temporal abnormalities have been described in such patients, but data are not consistently replicated, nor a univocal pathogenetic explanation of findings has been provided. Fine techniques like the cortical pattern matching (CPM) or the radial atrophy mapping are able to detect in great detail the morphology of the cortical gyri and the hippocampus, and might provide a detailed characterization of individuals coming from families carrying this kind of disease. Methods: MRI images from related subjects affected and non affected by mood disorders, and from matched healthy controls have been collected with 1.0 Tesla Philips Gyroscan (PG) in Brescia. Images were acquired with gradient echo 3D technique as follows: TR = 20 ms, TE = 5.0 ms, flip angle = 30[unreadable], field of view = 220 mm, acquisition matrix 256x256, slice thickness 1.3 mm. MRI images will be processed with two kinds of analysis: the cortical pattern matching technique and the hippocampal radial atrophy mapping. CPM: the algorithm will be used used to identify regions where the cortical gray matter density will be different in cases vs controls. MR images will be normalized to a customized template using a 12 parameter linear transformation and 3D cortical surfaces of both hemispheres will be extracted;29 sulci will be manually outlined on the lateral and medial surface of each hemisphere, and additional 3D lines will be drawn to delimit interhemispheric gyral limits. A customized template will be created averaging the traced sulci of the analyzed subjects, and the individual sulci will be used as landmarks to warp each subject's anatomy to the template. Original MR images will be segmented into gray matter, white matter, and CSF, and the warping fields obtained with cortical pattern matching will be applied to the GM images, thus allowing measurement of GM at thousands of homologous cortical locations. The mean gray matter proportion will be computed and a statistical significance map will be created using a t-test to compare affected patients vs non related controls, non affected relatives vs controls and affected patients vs non affected relatives. Hippocampal radial mapping: MRI images will be normalized by linear (12 parameter) transformation to a customized template using the Statistical Parametric Mapping (SPM99) software. The hippocampi will be manually traced according to a formal protocol with established inter- and intra-rater reliability and 3D parametric surface mesh models will be created to represent the hippocampus in each subject. To assess hippocampal morphology, a medial curve will be automatically defined as the 3D curve traced out by the centroid of the hippocampal boundary in each image slice. The radial size of each hippocampus at each boundary point will be assessed by automatically measuring the radial 3D distance from the surface points to the medial curve defined for individual's hippocampal surface model. Shorter radial distances will be used as an index of atrophy. Statistical maps will be generated indicating local group differences in radial hippocampal distance. Expected results: altered brain morphology, likely consisting in reduced volumes, is expected in the frontal lobes and in other structures, like the insular region, devoted to proper perception and control of emotional states. Altered morphology of the hippocampal formation is also expected, mainly in subjects with greater severity or frequency of depression episodes. Greater tissue reduction in the hippocampal subregions with greater concentration of corticosteroids receptors is expected.